{"id":"W4389084956","doi":"10.5194/egusphere-2023-2019-ac2","title":"Reply on RC1","year":2023,"lang":"en","type":"peer-review","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Leibniz-Rechenzentrum; Leibniz-Gemeinschaft; Environment and Climate Change Canada; Bayerische Akademie der Wissenschaften","keywords":"Flood myth; Precipitation; Extreme value theory; Environmental science; Climate change; Climatology; Return period; Generalized extreme value distribution; Intensity (physics); Maxima; Meteorology; Geography; Statistics; Mathematics; Geology; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002601825,0.0009121882,0.001040583,0.001013235,0.002857935,0.004073558,0.003284544,0.02793556,0.1477678],"category_scores_gemma":[0.03017913,0.000563862,0.001431287,0.0009648201,0.00210914,0.003588146,0.002582386,0.0240303,0.1171117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00355602,"about_ca_system_score_gemma":0.003408542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007064963,"about_ca_topic_score_gemma":0.007501718,"domain_scores_codex":[0.997163,0.0005432045,0.0002994416,0.0005499821,0.0009732191,0.0004711075],"domain_scores_gemma":[0.9933879,0.002165772,0.0002673423,0.000494665,0.00268212,0.001002117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000979328,0.000003433833,0.00003803849,0.00001573357,0.000001652993,0.00007171354,0.00001105796,0.000004592313,0.00001955085,0.0003431088,0.9975801,0.001901233],"study_design_scores_gemma":[0.00001106173,0.000007913836,0.0002121731,0.00006048305,0.000003057755,0.0000862135,0.00006514244,0.0000237209,0.00006289614,0.0005581863,0.998899,0.00001014402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0002685168,0.001636038,0.0002254256,0.7970389,0.1647985,0.0001176539,0.0006549566,0.000411187,0.03484877],"genre_scores_gemma":[0.002848914,0.0009816474,0.0002087438,0.8292891,0.05380545,0.0001984862,0.000255048,0.0001932903,0.1122193],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1477678,"threshold_uncertainty_score":0.4943326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03241635041228617,"score_gpt":0.2825835911227242,"score_spread":0.2501672407104381,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}